Point 431: 68 years old (2019)
Welch’s one-way test performed instead of ANOVA due to inhomogeneity of variances, looking for a significant age difference between years:
##
## One-way analysis of means (not assuming equal variances)
##
## data: patients$Age and as.factor(patients$Year)
## F = 0.68578, num df = 4.00, denom df = 277.99, p-value = 0.6023
| Indication | Mean age | Median age |
|---|---|---|
| IC | 64.0 | 65 |
| RP | 70.4 | 72 |
| TL | 72.0 | 73 |
Point 164: 73 years old (TL)
Welch’s one-way test performed instead of ANOVA due to inhomogeneity of variances:
##
## One-way analysis of means (not assuming equal variances)
##
## data: patients$Age and patients$Indication
## F = 25.446, num df = 2.00, denom df = 151.53, p-value = 2.963e-10
##
## Pairwise comparisons using t tests with non-pooled SD
##
## data: patients$Age and patients$Indication
##
## IC RP
## RP 0.00036 -
## TL 1.2e-10 0.26689
##
## P value adjustment method: BH
| Gender | Mean age | Median age |
|---|---|---|
| Man | 72.5 | 75 |
| Woman | 69.4 | 71 |
##
## Welch Two Sample t-test
##
## data: patients$Age by patients$Gender
## t = 3.2047, df = 427.3, p-value = 0.001453
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## 1.235113 5.153242
## sample estimates:
## mean in group Man mean in group Woman
## 72.54911 69.35493
##
## Kruskal-Wallis rank sum test
##
## data: procedures$Successful by as.factor(procedures$Year)
## Kruskal-Wallis chi-squared = 1.3559, df = 4, p-value = 0.8518
##
## Pairwise comparisons using Wilcoxon rank sum test
##
## data: procedures$Success and as.factor(procedures$Year)
##
## 2016 2017 2018 2019
## 2017 0.92 - - -
## 2018 0.92 0.92 - -
## 2019 0.92 0.92 0.97 -
## 2020 0.92 0.92 0.92 0.92
##
## P value adjustment method: BH
##
## Kruskal-Wallis rank sum test
##
## data: procedures$Successful by procedures$Indication
## Kruskal-Wallis chi-squared = 0.55031, df = 2, p-value = 0.7595
##
## Pairwise comparisons using Wilcoxon rank sum test
##
## data: procedures$Success and procedures$Indication
##
## IC RP
## RP 0.71 -
## TL 0.71 0.71
##
## P value adjustment method: BH
##
## Kruskal-Wallis rank sum test
##
## data: procedures$Successful by procedures$TASCII
## Kruskal-Wallis chi-squared = 49.491, df = 3, p-value = 1.026e-10
##
## Pairwise comparisons using Wilcoxon rank sum test
##
## data: procedures$Success and procedures$TASCII
##
## A B C
## B 0.9602 - -
## C 0.0388 0.0129 -
## D 1.6e-07 1.1e-10 0.0034
##
## P value adjustment method: BH
Overall, including failed procedures, 79% of treatments leave nothing behind
More specific devices:
| Yes/No | Iliac | CFA | P3 | Crural | Lysis |
|---|---|---|---|---|---|
| No | 696.0 | 672.0 | 586.0 | 533.0 | 706.0 |
| Yes | 23.0 | 47.0 | 133.0 | 186.0 | 13.0 |
| % Yes | 3.2 | 6.5 | 18.5 | 25.9 | 1.8 |
| Number of complexity markers | Number | Percentage |
|---|---|---|
| 0 | 420 | 58.4 |
| 1 | 203 | 28.2 |
| 2 | 89 | 12.4 |
| 3 | 7 | 1.0 |
##
## Kruskal-Wallis rank sum test
##
## data: procedures$Successful by procedures$multiComp
## Kruskal-Wallis chi-squared = 6.5881, df = 3, p-value = 0.08625
##
## Pairwise comparisons using Wilcoxon rank sum test
##
## data: procedures$Success and procedures$multiComp
##
## 0 1 2
## 1 0.099 - -
## 2 0.533 0.533 -
## 3 0.533 0.533 0.533
##
## P value adjustment method: BH
Death dates were last checked 17/04/2020
Log-rank test is used to sompare survival estimates between groups
## Warning: Vectorized input to `element_text()` is not officially supported.
## Results may be unexpected or may change in future versions of ggplot2.
##
## Pairwise comparisons using Log-Rank test
##
## data: patients and Year
##
## 2016 2017 2018 2019
## 2017 0.94 - - -
## 2018 0.94 0.94 - -
## 2019 0.98 0.94 0.98 -
## 2020 0.94 0.94 0.94 0.94
##
## P value adjustment method: BH
## Warning: Vectorized input to `element_text()` is not officially supported.
## Results may be unexpected or may change in future versions of ggplot2.
##
## Pairwise comparisons using Log-Rank test
##
## data: patients and TASCII
##
## A B C
## B 0.00031 - -
## C 1.4e-06 0.03079 -
## D 0.00011 0.14135 0.89372
##
## P value adjustment method: BH
## Warning: Vectorized input to `element_text()` is not officially supported.
## Results may be unexpected or may change in future versions of ggplot2.
##
## Pairwise comparisons using Log-Rank test
##
## data: patients and Gender
##
## Man
## Woman 0.72
##
## P value adjustment method: BH
## Warning: Vectorized input to `element_text()` is not officially supported.
## Results may be unexpected or may change in future versions of ggplot2.
##
## Pairwise comparisons using Log-Rank test
##
## data: patients and Indication
##
## IC RP
## RP 1.6e-05 -
## TL 1.1e-09 0.014
##
## P value adjustment method: BH
## Warning: Vectorized input to `element_text()` is not officially supported.
## Results may be unexpected or may change in future versions of ggplot2.
##
## Pairwise comparisons using Log-Rank test
##
## data: patients and Successful
##
## No
## Yes 0.0046
##
## P value adjustment method: BH
## Warning: Vectorized input to `element_text()` is not officially supported.
## Results may be unexpected or may change in future versions of ggplot2.
##
## Pairwise comparisons using Log-Rank test
##
## data: patients and Dev
##
## Bal St
## St 0.753 -
## Fail 0.013 0.058
##
## P value adjustment method: BH
## Warning: Vectorized input to `element_text()` is not officially supported.
## Results may be unexpected or may change in future versions of ggplot2.
##
## Pairwise comparisons using Log-Rank test
##
## data: patients and multiComp
##
## 0 1 2
## 1 0.73 - -
## 2 0.73 0.73 -
## 3 0.73 0.73 0.73
##
## P value adjustment method: BH
## Warning: Vectorized input to `element_text()` is not officially supported.
## Results may be unexpected or may change in future versions of ggplot2.
##
## Pairwise comparisons using Log-Rank test
##
## data: tlPat and TASCII
##
## A B C
## B 0.0199 - -
## C 0.0023 0.1099 -
## D 0.0155 0.3987 0.8733
##
## P value adjustment method: BH
## Warning: Vectorized input to `element_text()` is not officially supported.
## Results may be unexpected or may change in future versions of ggplot2.
##
## Pairwise comparisons using Log-Rank test
##
## data: tlPat and Gender
##
## Man
## Woman 0.53
##
## P value adjustment method: BH
## Warning: Vectorized input to `element_text()` is not officially supported.
## Results may be unexpected or may change in future versions of ggplot2.
##
## Pairwise comparisons using Log-Rank test
##
## data: tlPat and Successful
##
## No
## Yes 0.004
##
## P value adjustment method: BH
## Warning: Vectorized input to `element_text()` is not officially supported.
## Results may be unexpected or may change in future versions of ggplot2.
##
## Pairwise comparisons using Log-Rank test
##
## data: tlPat and Dev
##
## Bal St
## St 0.895 -
## Fail 0.012 0.048
##
## P value adjustment method: BH
## Warning: Vectorized input to `element_text()` is not officially supported.
## Results may be unexpected or may change in future versions of ggplot2.
##
## Pairwise comparisons using Log-Rank test
##
## data: tlPat and multiComp
##
## 0 1 2
## 1 0.55 - -
## 2 0.55 0.55 -
## 3 0.55 0.55 0.55
##
## P value adjustment method: BH
## Warning: Vectorized input to `element_text()` is not officially supported.
## Results may be unexpected or may change in future versions of ggplot2.
##
## Pairwise comparisons using Log-Rank test
##
## data: patients and Indication
##
## IC RP
## RP 1.000 -
## TL 0.088 0.088
##
## P value adjustment method: BH
Amputation dates were last checked 22/06/2020
Log-rank test is used to compare amputation survival estimates between groups
## Warning: Vectorized input to `element_text()` is not officially supported.
## Results may be unexpected or may change in future versions of ggplot2.
##
## Pairwise comparisons using Log-Rank test
##
## data: limbs and Year
##
## 2016 2017 2018 2019
## 2017 0.884 - - -
## 2018 0.055 0.066 - -
## 2019 0.673 0.483 0.033 -
## 2020 0.055 0.055 0.682 0.033
##
## P value adjustment method: BH
## Warning: Vectorized input to `element_text()` is not officially supported.
## Results may be unexpected or may change in future versions of ggplot2.
##
## Pairwise comparisons using Log-Rank test
##
## data: limbs and TASCII
##
## A B C
## B 0.02242 - -
## C 0.06906 0.95016 -
## D 0.00033 0.03848 0.06906
##
## P value adjustment method: BH
## Warning: Vectorized input to `element_text()` is not officially supported.
## Results may be unexpected or may change in future versions of ggplot2.
##
## Pairwise comparisons using Log-Rank test
##
## data: patients and Gender
##
## Man
## Woman 0.0053
##
## P value adjustment method: BH
## Warning: Vectorized input to `element_text()` is not officially supported.
## Results may be unexpected or may change in future versions of ggplot2.
##
## Pairwise comparisons using Log-Rank test
##
## data: limbs and Indication
##
## IC RP
## RP 0.00014 -
## TL 1.5e-06 0.10276
##
## P value adjustment method: BH
## Warning: Vectorized input to `element_text()` is not officially supported.
## Results may be unexpected or may change in future versions of ggplot2.
##
## Pairwise comparisons using Log-Rank test
##
## data: limbs and Successful
##
## No
## Yes 0.14
##
## P value adjustment method: BH
## Warning: Vectorized input to `element_text()` is not officially supported.
## Results may be unexpected or may change in future versions of ggplot2.
##
## Pairwise comparisons using Log-Rank test
##
## data: limbs and Dev
##
## Bal St
## St 0.43 -
## Fail 0.29 0.29
##
## P value adjustment method: BH
## Warning: Vectorized input to `element_text()` is not officially supported.
## Results may be unexpected or may change in future versions of ggplot2.
##
## Pairwise comparisons using Log-Rank test
##
## data: limbs and multiComp
##
## 0 1 2
## 1 0.729 - -
## 2 0.086 0.178 -
## 3 0.357 0.357 0.729
##
## P value adjustment method: BH
## Warning: Vectorized input to `element_text()` is not officially supported.
## Results may be unexpected or may change in future versions of ggplot2.
##
## Pairwise comparisons using Log-Rank test
##
## data: tlLimb and TASCII
##
## A B C
## B 0.0665 - -
## C 0.2443 0.5126 -
## D 0.0063 0.0983 0.0983
##
## P value adjustment method: BH
## Warning: Vectorized input to `element_text()` is not officially supported.
## Results may be unexpected or may change in future versions of ggplot2.
##
## Pairwise comparisons using Log-Rank test
##
## data: tlLimb and Gender
##
## Man
## Woman 0.0018
##
## P value adjustment method: BH
## Warning: Vectorized input to `element_text()` is not officially supported.
## Results may be unexpected or may change in future versions of ggplot2.
##
## Pairwise comparisons using Log-Rank test
##
## data: tlLimb and Successful
##
## No
## Yes 0.072
##
## P value adjustment method: BH
## Warning: Vectorized input to `element_text()` is not officially supported.
## Results may be unexpected or may change in future versions of ggplot2.
##
## Pairwise comparisons using Log-Rank test
##
## data: tlLimb and Dev
##
## Bal St
## St 0.57 -
## Fail 0.15 0.15
##
## P value adjustment method: BH
## Warning: Vectorized input to `element_text()` is not officially supported.
## Results may be unexpected or may change in future versions of ggplot2.
##
## Pairwise comparisons using Log-Rank test
##
## data: tlLimb and multiComp
##
## 0 1 2
## 1 0.28 - -
## 2 0.47 0.28 -
## 3 0.47 0.28 0.47
##
## P value adjustment method: BH
## Warning: Vectorized input to `element_text()` is not officially supported.
## Results may be unexpected or may change in future versions of ggplot2.
##
## Pairwise comparisons using Log-Rank test
##
## data: limbs and Indication
##
## IC RP
## RP 0.006 -
## TL 0.006 0.719
##
## P value adjustment method: BH